Biomass burning (BB) is a significant source of particulate matter (PM) in many parts of the world. Whereas numerous studies demonstrate the relevance of BB emissions in central and northern Europe, the quantification of this source has been assessed only in few cities in southern European countries. In this work, the application of Positive Matrix Factorisation (PMF) allowed a clear identification and quantification of an unexpected very high biomass burning contribution in Tuscany (central Italy), in the most polluted site of the PATOS project. In this urban background site, BB accounted for 37% of the mass of PM10 (particulate matter with aerodynamic diameter<10 μm) as annual average, and more than 50% during winter, being the main cause of all the PM10 limit exceedances. Due to the chemical complexity of BB emissions, an accurate assessment of this source contribution is not always easily achievable using just a single tracer. The present work takes advantage of the combination of a long-term daily data-set, characterized by an extended chemical speciation, with a short-term high time resolution (1-hour) and size-segregated data-set, obtained by PIXE analyses of streaker samples. The hourly time pattern of the BB source, characterised by a periodic behaviour with peaks starting at about 6 p.m. and lasting all the evening-night, and its strong seasonality, with higher values in the winter period, clearly confirmed the hypothesis of a domestic heating source (also excluding important contributions from wildfires and agricultural wastes burning).